1. Chronic nicotine exposure reduces reward-related activity in the striatum but not the midbrain: The reinforcing effects of nicotine are mediated by brain regions that also support temporal difference error (TDE) processing, yet the impact of nicotine on TDE is undetermined. Dependent smokers and matched controls were trained to associate a juice reward with a visual cue in a classical conditioning paradigm. Smokers received a 21mg nicotine or placebo patch before scanning. A reduction was seen in TDE-related function in smokers in the striatum, which did not differ based on patch manipulation, but was predicted by years of smoking. Activation in midbrain regions was not impacted by group or drug condition. These data suggest a differential effect of smoking status on the neural substrates of reward in distinct dopaminergic pathway regions, possibly partially due to chronic nicotine use. The failure of nicotine to alter reward-related functional processes either within smokers or between smokers and controls implies that acute nicotine administration is insufficient to modify reward processing, which has been linked to abstinence induced anhedonia in smokers and may play a critical role in relapse. 2. Neurocognitive effects of Varenicline and nicotine in acutely abstinent smokers: Clinical trials have shown that varenicline helps about 45% of smokers quit while on medication, suggesting individual differences in efficacy. Elucidating potential differential responses to currently available pharmacological aids may expedite development of personalized treatments based on endophenotypic characteristics. Varenicline is thought to reduce smoking behaviors by ameliorating withdrawal following nicotine abstinence, while also dampening transient, nicotine-induced effects following nicotine delivery. The amygdala is linked with negative affective states accompanying acute withdrawal. We studied the impact of varenicline in the presence and absence of nicotine to elucidate its effect on amygdala reactivity. Abstinence-induced alterations on amygdala reactivity was reduced by varenicline and nicotine. fMRI data from a task exploring regional brain activity to positive and negative feedback also indicate differential responses in regions important for rewarding processing (ventral striatum) and error processing (ACC, insula, habenula). Such differential brain and behavioral effects could be used to identify which smokers would benefit most from varenicline treatment. 3. Nicotine and prefrontal dopamine regulate activation in a cortico-striatal network in smokers during reward processing, implications for nicotine replacement therapy: People with the Val allele of the functional catechol-O-methyltransferase (COMT) Val158Met polymorphism have greater nicotine dependence and poorer outcomes in smoking cessation trials with nicotine replacement therapy (NRT) compared to those with the Met allele. Given that nicotine and tonic DA (as inferred by COMT genotype) may interact to affect prefrontal processing and that nicotine moderates DA-related reward processing, we examined whether there is a similar nicotine x COMT genotype interaction for reward processing in smokers. The MID task was used to probe brain circuitry for reward processing in smokers. There was a significant nicotine x COMT genotype interaction for BOLD signal during outcome in dorsal striatum, medial frontal and inferior frontal gyri such that activation in the presence of nicotine in these areas increased in homozygotes and decreased in Met allele carriers. Further, during negative performance feedback, significant activation of error monitoring areas such as ACC/superior frontal gyrus occurred only in homozygotes with nicotine. These data suggest a possible mechanism underlying the clinical observation that homozygotes have poorer outcomes with NRT. Specifically, with nicotine administration, this genotype group activated dorsal striatal, habit learning areas in response to performance feedback, while in response to negative feedback, they activated error monitoring areas, including the ACC, suggesting increased sensitivity to loss with nicotine exposure. 4. Anatomical differences and network characteristics underlying smoking cue reactivity: A distributed network of brain regions is linked to drug-related cue responding but, the relationships between smoking cue-induced phasic activity and differences in brain structure, tonic neuronal activity and connectivity between these regions are unclear. Smokers and controls viewed smoking-related and neutral pictures during fMRI scanning. Dorsal lateral and dorsomedial prefrontal cortex (dlPFC, dmPFC), dorsal anterior cingulate cortex (dACC), rostral ACC (rACC), occipital cortex, and insula, showed significant smoking cue-elicited activity in smokers. rsFC strength between rACC and dlPFC was positively correlated with the cue-elicited activity in dlPFC. Similarly, rsFC strength between dlPFC and dmPFC was positively correlated with the cue-elicited activity in dmPFC while rsFC strength between dmPFC and insula was negatively correlated with the cue-elicited activity in both dmPFC and insula, suggesting these brain circuits may facilitate the response to salient smoking cues. Further, gray matter density in dlPFC was decreased in smokers and correlated with cue-elicited activity, suggesting a neurobiological mechanism for the impaired cognitive control associated with drug use. These results begin to address the underlying neurobiology of smoking cue response, and may speak to novel treatment strategies and targets for therapeutic interventions. 5. Factors underlying prefrontal and insula structural alterations in smokers: We examined alterations in white matter integrity (fractional anisotropyFA) and gray matter density (voxel-based morphometry (VBM) in smokers. Gray matter density was lower in left PFC in high smokers with the highest use history and was inversely related to use. In contrast, left insular cortex gray matter density was higher in smokers and associated with TAS-20 total score and with difficulty-identifying-feelings factor. Further, the most highly dependent smokers showed lower prefrontal FA, which was negatively correlated with dependence severity. These data suggest chronic tobacco use is associated with prefrontal gray matter pathology, while differences in insula gray matter and PFC white matter appear to reflect stable and heritable differences between smokers and non-smokers. 6. Chronic smoking modulates neural correlates of working memory: The cognitive-enhancing properties of nicotine on WM operations remain unclear. We explored the impact of nicotine administration on neural functioning in smokers and also assessed differences between smokers and controls. Subjects were required to simultaneously maintain, and frequently switch attentional focus between 2 running tallies in WM. In both groups, bilateral activation was seen notably in medial and lateral PFC, anterior insula, and parietal regions, whereas individual attentional switch trials were associated with activation in a similar, but predominantly left-lateralized network. Smokers showed greater tonic activation in medial superior frontal cortex, anterior insula, and anterior PFC throughout task blocks (trait-like effect). These data suggest smokers require recruitment of additional WM and supervisory control operations during task performance.